Control architecture and operator interface for a free-flying robotic vehicle

Space and underwater vehicles with robotic arms can severely tax the capability of conventional control systems. Submersible vehicles used in neutral buoyancy simulation are subject to even greater demands since they must simulate the dynamics of spacecraft in orbit as well as function as a remotely-operated underwater vehicle. In this report, the onboard control architecture, human-machine interface, and vehicle/operator communications are described for one such vehicle in operation at the University of Maryland Neutral Buoyancy Research Facility (NBRF). The Ranger Neutral Buoyancy Vehicle (RNBV) exemplifies the high-dimensional, computationally intensive nature of the current fleet of autonomous underwater vehicles while its complement of four manipulators exceeds the capabilities of most remotely operated vehicles in service today. The sensor-based, embedded onboard control system is described, and its implementation using multiple control stations is discussed.

[1]  Mark S. Sanders,et al.  Human Factors in Engineering and Design , 2016 .

[2]  B. Schneiderman,et al.  Designing the User Interface. Strategies for Effective Human-Computer Interaction , 1992 .

[3]  Craig R. Carignan,et al.  Dynamic tool vectors for robo-centric control , 2000, Proceedings 2000 ICRA. Millennium Conference. IEEE International Conference on Robotics and Automation. Symposia Proceedings (Cat. No.00CH37065).

[4]  Samad Hayati,et al.  Design and implementation of a robot control system with traded and shared control capability , 1989, Proceedings, 1989 International Conference on Robotics and Automation.

[5]  Junku Yuh,et al.  Underwater robotics , 2000, Proceedings 2000 ICRA. Millennium Conference. IEEE International Conference on Robotics and Automation. Symposia Proceedings (Cat. No.00CH37065).

[6]  John J. Craig,et al.  Introduction to Robotics Mechanics and Control , 1986 .

[7]  Joseph C. Parrish Ranger telerobotic shuttle experiment (RTSX): status report , 1998, Other Conferences.

[8]  O. Egeland,et al.  Passivity-based adaptive attitude control of a rigid spacecraft , 1994, IEEE Trans. Autom. Control..

[9]  Craig R. Carignan,et al.  Reconfigurable control station design for robotic operations , 1997, 1997 IEEE International Conference on Systems, Man, and Cybernetics. Computational Cybernetics and Simulation.

[10]  R. Lakshmi,et al.  A coordinated control of an underwater vehicle and robotic manipulator , 1991, J. Field Robotics.

[11]  Craig R. Carignan,et al.  Achieving impedance objectives in robot teleoperation , 1997, Proceedings of International Conference on Robotics and Automation.

[12]  Bong Wie,et al.  Quaternion feedback for spacecraft large angle maneuvers , 1985 .

[13]  Ben Shneiderman,et al.  Designing the User Interface: Strategies for Effective Human-Computer Interaction , 1998 .

[14]  Robert Sanner,et al.  Adaptive attitude control using fixed and dynamically structured neural networks , 1996 .

[15]  J. Robert Fricke,et al.  Down to the sea in robots , 1994 .

[16]  Maja Matijasevic,et al.  Control architectures for autonomous underwater vehicles , 1997 .

[17]  G. A. Miller THE PSYCHOLOGICAL REVIEW THE MAGICAL NUMBER SEVEN, PLUS OR MINUS TWO: SOME LIMITS ON OUR CAPACITY FOR PROCESSING INFORMATION 1 , 1956 .

[18]  David L. Akin,et al.  Real-time simulation of a free-flying robotic vehicle , 1999 .

[19]  Craig R. Carignan,et al.  The reaction stabilization of on-orbit robots , 2000 .

[20]  Craig R. Carignan,et al.  A partitioned redundancy management scheme for an eight‐joint revolute manipulator , 2000 .

[21]  Phillip J. McKerrow,et al.  Introduction to robotics , 1991 .

[22]  Thor I. Fossen,et al.  Guidance and control of ocean vehicles , 1994 .